An increasing number of genes which play a role in many different diseases are being identified. Detection of mutations in such genes is instrumental in determining susceptibility to or diagnosing these diseases. Some diseases, such as sickle cell disease, are monomorphic, i.e., the disease is generally caused by a single mutation present in the population. In such cases where one or only a few known mutations are responsible for the disease, methods for detecting the mutations are targeted to the site within the gene at which they are known to occur.
In many other cases, however, individuals affected by a given disease display extensive allelic heterogeneity. For example, more than 125 mutations in the human BRCA1 gene have been reported (Breast Cancer Information Core world wide web site at http://www.nchgr.nih.gov/dir/lab.sub.-- transfer/bic, which became publicly available on Nov. 1, 1995; Friend, S. et al., 1995, Nature Genetics 11: 238). Mutations in the BRCA1 gene are thought to account for roughly 45% of inherited breast cancer and 80-90% of families with increased risk of early onset breast and ovarian cancer (Easton, 1993, et al., American Journal of Human Genetics 52: 678-701).
Other examples of genes for which the population displays extensive allelic heterogeneity and which have been implicated in disease include CFTR (cystic fibrosis), dystrophin (Duchenne muscular dystrophy, and Becker muscular dystrophy), and p53 (Li-Fraumeni syndrome).
Breast cancer is also an example of a disease in which, in addition to allelic heterogeneity, there is genetic heterogeneity. In addition to BRCA1, the BRCA2 and BRCA3 genes have been linked to breast cancer. Similarly, the NFI and NFII genes are involved in neurofibromatosis (types I and II, respectively).
Accuracy in detection of mutations is extremely important, particularly in clinical settings. Direct end-to-end sequencing of the gene potentially provides the most accurate results, given that an accurate reference sequence is available. However, sequencing can also be a cumbersome technique. Detection of one of many known or unknown mutations is further complicated when the gene is large and/or has a complex structure. The human BRCA1 gene, for example, is approximately 100,000 base pairs long and contains 24 exons (Weber, B., Science and Medicine, Scientific American January-February 1996, 12-21). Furthermore, in order to be practical and available to the general population, detection methods must be efficient enough to accommodate a large number of different samples.
A number of techniques that are more rapid but less comprehensive than direct sequencing have been developed for detecting nucleotide sequence variations. Many of these techniques are based on detecting differences, between normal and mutant nucleotide sequences, in hybridization (e.g., allele specific hybridization), secondary structure (e.g., single strand conformation polymorphism analysis, heteroduplex analysis), melting (constant denaturing gel electrophoresis, denaturing gradient gel electrophoresis), and susceptibility to cleavage (either chemical or restriction enzyme cleavage). Other techniques, such as the protein truncation test, detect changes on the protein level. For a summary of such techniques, see Marajver & Petty, 1996, Clinics in Lab. Med. 16: 139-167, especially Table 5 at p. 152.
Efforts have independently focused primarily on increasing the rapidity of processing sequencing analyses or increasing the comprehensiveness of the hybridization-based techniques. There remains a need, however, for a systematic method of detecting mutations in individual gene samples that is both accurate enough to provide a reliable diagnosis to an individual patient and efficient enough to be practical for application to the general population.